Glutamatergic synapse in autism: a complex story for a complex disorder.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder whose pathophysiological mechanisms are still unclear. Hypotheses suggest a role for glutamate dysfunctions in ASD development, but clinical studies investigating brain and peripheral glutamate levels showed heterogenous results leading to hypo- and hyper-glutamatergic hypotheses of ASD. Recently, studies proposed the implication of elevated mGluR5 densities in brain areas in the pathophysiology of ASD. Thus, our objective was to characterize glutamate dysfunctions in adult subjects with ASD by quantifying (1) glutamate levels in the cingulate cortex and periphery using proton magnetic resonance spectroscopy and metabolomics, and (2) mGluR5 brain density in this population and in a validated animal model of ASD (prenatal exposure to valproate) at developmental stages corresponding to childhood and adolescence in humans using positron emission tomography. No modifications in cingulate Glu levels were observed between individuals with ASD and controls further supporting the difficulty to evaluate modifications in excitatory transmission using spectroscopy in this population, and the complexity of its glutamate-related changes. Our imaging results showed an overall increased density in mGluR5 in adults with ASD, that was only observed mostly subcortically in adolescent male rats prenatally exposed to valproic acid, and not detected in the stage corresponding to childhood in the same animals. This suggest that clinical changes in mGluR5 density could reflect the adaptation of the glutamatergic dysfunctions occurring earlier rather than being key to the pathophysiology of ASD.

Maternal Rat Metabolomics: Amniotic Fluid and Placental Metabolic Profiling Workflows.

Studying the metabolome of specific gestational compartments is of growing interest in the context of fetus developmental disorders. However, the metabolomes of the placenta and amniotic fluid (AF) are poorly characterized. Therefore, we present the validation of a fingerprinting methodology. Using pregnant rats, we performed exhaustive and robust extractions of metabolites in the AF and lipids and more polar metabolites in the placenta. For the AF, we compared the extraction capabilities of methanol (MeOH), acetonitrile (ACN), and a mixture of both. For the placenta, we compared (i) the extraction capabilities of dichloromethane, methyl t-butyl ether (MTBE), and butanol, along with (ii) the impact of lyophilization of the placental tissue. Analyses were performed on a C18 and hydrophilic interaction liquid chromatography combined with high-resolution mass spectrometry. The efficiency and the robustness of the extractions were compared based on the number of the features or metabolites (for untargeted or targeted approach, respectively), their mean total intensity, and their coefficient of variation (% CV). The extraction capabilities of MeOH and ACN on the AF metabolome were equivalent. Lyophilization also had no significant impact and usefulness on the placental tissue metabolome profiling. Considering the placental lipidome, MTBE extraction was more informative because it allowed extraction of a slightly higher number of lipids, in higher concentration. This proof-of-concept study assessing the metabolomics and lipidomics of the AF and the placenta revealed changes in both metabolisms, at two different stages of rat gestation, and allowed a detailed prenatal metabolic fingerprinting.

Optimization of Sample Preparation for Metabolomics Exploration of Urine, Feces, Blood and Saliva in Humans Using Combined NMR and UHPLC-HRMS Platforms.

Currently, most clinical studies in metabolomics only consider a single type of sample such as urine, plasma, or feces and use a single analytical platform, either NMR or MS. Although some studies have already investigated metabolomics data from multiple fluids, the information is limited to a unique analytical platform. On the other hand, clinical studies investigating the human metabolome that combine multi-analytical platforms have focused on a single biofluid. Combining data from multiple sample types for one patient using a multimodal analytical approach (NMR and MS) should extend the metabolome coverage. Pre-analytical and analytical phases are time consuming. These steps need to be improved in order to move into clinical studies that deal with a large number of patient samples. Our study describes a standard operating procedure for biological specimens (urine, blood, saliva, and feces) using multiple platforms (1H-NMR, RP-UHPLC-MS, and HILIC-UHPLC-MS). Each sample type follows a unique sample preparation procedure for analysis on a multi-platform basis. Our method was evaluated for its robustness and was able to generate a representative metabolic map.

Wildtype motoneurons, ALS-Linked SOD1 mutation and glutamate profoundly modify astrocyte metabolism and lactate shuttling.

The selective degeneration of motoneuron that typifies amyotrophic lateral sclerosis (ALS) implicates non-cell-autonomous effects of astrocytes. However, mechanisms underlying astrocyte-mediated neurotoxicity remain largely unknown. According to the determinant role of astrocyte metabolism in supporting neuronal function, we propose to explore the metabolic status of astrocytes exposed to ALS-associated conditions. We found a significant metabolic dysregulation including purine, pyrimidine, lysine, and glycerophospholipid metabolism pathways in astrocytes expressing an ALS-causing mutated superoxide dismutase-1 (SOD1) when co-cultured with motoneurons. SOD1 astrocytes exposed to glutamate revealed a significant modification of the astrocyte metabolic fingerprint. More importantly, we observed that SOD1 mutation and glutamate impact the cellular shuttling of lactate between astrocytes and motoneurons with a decreased in extra- and intra-cellular lactate levels in astrocytes. Based on the emergent strategy of metabolomics, this work provides novel insight for understanding metabolic dysfunction of astrocytes in ALS conditions and opens the perspective of therapeutics targets through focusing on these metabolic pathways. GLIA 2017 GLIA 2017;65:592-605.

Metabolomics Study of Urine in Autism Spectrum Disorders Using a Multiplatform Analytical Methodology.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with no clinical biomarker. The aims of this study were to characterize a metabolic signature of ASD and to evaluate multiplatform analytical methodologies in order to develop predictive tools for diagnosis and disease follow-up. Urine samples were analyzed using (1)H and (1)H-(13)C NMR-based approaches and LC-HRMS-based approaches (ESI+ and ESI- on HILIC and C18 chromatography columns). Data tables obtained from the six analytical modalities on a training set of 46 urine samples (22 autistic children and 24 controls) were processed by multivariate analysis (orthogonal partial least-squares discriminant analysis, OPLS-DA). The predictions from each of these OPLS-DA models were then evaluated using a prediction set of 16 samples (8 autistic children and 8 controls) and receiver operating characteristic curves. Thereafter, a data fusion block-scaling OPLS-DA model was generated from the 6 best models obtained for each modality. This fused OPLS-DA model showed an enhanced performance (R(2)Y(cum) = 0.88, Q(2)(cum) = 0.75) compared to each analytical modality model, as well as a better predictive capacity (AUC = 0.91, p-value = 0.006). Metabolites that are most significantly different between autistic and control children (p < 0.05) are indoxyl sulfate, N-α-acetyl-l-arginine, methyl guanidine, and phenylacetylglutamine. This multimodality approach has the potential to contribute to find robust biomarkers and characterize a metabolic phenotype of the ASD population.

Analytical methodology for metabolomics study of adherent mammalian cells using NMR, GC-MS and LC-HRMS.

We developed a methodology for the analysis of intracellular metabolites using nuclear magnetic resonance spectrometry (NMR), gas-chromatography coupled with mass spectrometry (GC-MS), and liquid chromatography coupled with high resolution mass spectrometry (LC-HRMS). The main steps for analysis of adherent cells in order to recover the widest possible range of intracellular compounds are blocking metabolic activity by quenching and extraction of intracellular metabolites. We explored three protocols to quench NSC-34 cell metabolism and four different extraction methods, analyzed by NMR. On the basis of the number of metabolites extracted and their relative standard deviation (RSD) analyzed by NMR, the most reproducible protocol [quenching by MeOH at -40 °C and extraction with CH2Cl2/MeOH/H2O (3:3:2)] was used to obtain intracellular media to be analyzed by GC-MS and LC-HRMS. GC-MS analysis was optimized by three oximation procedures followed by silylation derivatization and these were compared to silylation alone. Using reversed-phase liquid chromatography (C18), four different gradients for LC-MS were compared. The analytical protocols were determined to establish the reliability and suitability of sample treatments required to achieve the correct biological analysis of untargeted mammalian cell metabolomics.

Combined 1H-NMR and 1H-13C HSQC-NMR to improve urinary screening in autism spectrum disorders.

Autism spectrum disorders (ASD) are neurodevelopmental diseases with complex genetic and environmental etiological factors. Although genetic causes play a significant part in the etiology of ASD, metabolic disturbances may also play a causal role or modulate the clinical features of ASD. The number of ASD studies involving metabolomics is increasing, and sometime with conflicting findings. We assessed the metabolomics profiling of urine samples to determine a comprehensive biochemical signature of ASD. Furthermore, to date no study has combined metabolic profiles obtained from different analytical techniques to distinguish patient with ASD from healthy individuals. We obtained (1)H-NMR spectra and 2D (1)H-(13)C HSQC NMR spectra from urine samples of patients with ASD or healthy controls. We analyzed these spectra by multivariate statistical data analysis. The OPLS-DA model obtained from (1)H NMR spectra showed a good discrimination between ASD samples and non-ASD samples (R(2)Y(cum) = 0.70 and Q(2) = 0.51). Combining the (1)H NMR spectra and the 2D (1)H-(13)C HSQC NMR spectra increased the overall quality and predictive value of the OPLS-DA model (R(2)Y(cum) = 0.84 and Q(2) = 0.71), leading to a better sensitivity and specificity. Urinary excretion of succinate, glutamate and 3-methyl-histidine differed significantly between ASD and non-ASD samples. Urinary screening of children with neurodevelopmental disorders by combining NMR spectroscopies (1D and 2D) in multivariate analysis is a better sensitive and a straightforward method that could help the diagnosis ASD.

Temporal metabolomics state in pregnant rat: Analysis of amniotic fluid, placenta, and maternal plasma at embryonic and fetal time points.

INTRODUCTION: During pregnancy, the dynamic metabolic demands for fetal growth require a continuous supply of essential metabolites. Understanding maternal metabolome changes during gestation is crucial for predicting disease risks in neonates. METHODS: The study aimed to characterize the placental and amniotic fluid (AF) metabolomes during gestation in rats at gestational days GD-13 and 19 reflecting the end of the embryonic and fetal periods, respectively, and the maternal plasma, using metabolomics (LC-MS) and chemometrics. The objective was to highlight, through univariate and multivariate analyses, the complementarity of the data obtained from these different biological matrices. RESULTS: The biological matrix had more impact on the metabolome composition than the gestational stage. The placental and AF metabolomes showed specific metabolome evolving over the two gestational stages. Analyzing the three targeted metabolomes revealed evolving pathways in arginine and proline metabolism/glutathione metabolism and phenylalanine metabolism; purine metabolism; and carbohydrate metabolism. Significantly, lipid metabolism in the placenta exhibited substantial changes with higher levels of certain phosphatidylethanolamine and sphingomyelins at GD19 while some cholesteryl esters and some glycosphingolipids levels being in higher levels at GD13. DISCUSSION: These data highlight the metabolic gradients (mainly in placenta, also in AF, but only a few in plasma) observed through embryonic patterning and organ development during mid-to late gestation.

Metabolomics in cerebrospinal fluid of patients with amyotrophic lateral sclerosis: an untargeted approach via high-resolution mass spectrometry.

Amyotrophic lateral sclerosis (ALS) is characterized by the absence of reliable diagnostic biomarkers. The aim of the study was to (i) devise an untargeted metabolomics methodology that reliably compares cerebrospinal fluid (CSF) from ALS patients and controls by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS); (ii) ascertain a metabolic signature of ALS by use of the LC-HRMS platform; (iii) identify metabolites for use as diagnostic or pathophysiologic markers. We developed a method to analyze CSF components by UPLC coupled with a Q-Exactive mass spectrometer that uses electrospray ionization. Metabolomic profiles were created from the CSF obtained at diagnosis from ALS patients and patients with other neurological conditions. We performed multivariate analyses (OPLS-DA) and univariate analyses to assess the contribution of individual metabolites as well as compounds identified in other studies. Sixty-six CSF samples from ALS patients and 128 from controls were analyzed. Metabolome analysis correctly predicted the diagnosis of ALS in more than 80% of cases. OPLS-DA identified four features that discriminated diagnostic group (p < 0.004). Our data demonstrate that untargeted metabolomics with LC-HRMS is a robust procedure to generate a specific metabolic profile for ALS from CSF and could be an important aid to the development of biomarkers for the disease.

GC-MS-based urine metabolic profiling of autism spectrum disorders.

Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders resulting from multiple factors. Diagnosis is based on behavioural and developmental signs detected before 3 years of age, and there is no reliable biological marker. The purpose of this study was to evaluate the value of gas chromatography combined with mass spectroscopy (GC-MS) associated with multivariate statistical modeling to capture the global biochemical signature of autistic individuals. GC-MS urinary metabolic profiles of 26 autistic and 24 healthy children were obtained by liq/liq extraction, and were or were not subjected to an oximation step, and then were subjected to a persilylation step. These metabolic profiles were then processed by multivariate analysis, in particular orthogonal partial least-squares discriminant analysis (OPLS-DA, R(2)Y(cum) = 0.97, Q(2)(cum) = 0.88). Discriminating metabolites were identified. The relative concentrations of the succinate and glycolate were higher for autistic than healthy children, whereas those of hippurate, 3-hydroxyphenylacetate, vanillylhydracrylate, 3-hydroxyhippurate, 4-hydroxyphenyl-2-hydroxyacetate, 1H-indole-3-acetate, phosphate, palmitate, stearate, and 3-methyladipate were lower. Eight other metabolites, which were not identified but characterized by a retention time plus a quantifier and its qualifier ion masses, were found to differ between the two groups. Comparison of statistical models leads to the conclusion that the combination of data obtained from both derivatization techniques leads to the model best discriminating between autistic and healthy groups of children.

QSAR study and synthesis of new phenyltropanes as ligands of the dopamine transporter (DAT).

The dopamine transporter (DAT) plays a pivotal role in the regulation of dopamine neurotransmission, and is involved in a number of physiological functions and brain disorders. Furthermore the DAT analysis by molecular imaging techniques is a useful tool for the diagnosis and follow up treatment of diseases involving the DAT. In order to predict the affinity of new derivatives for the DAT, different QSAR molecular modeling models based on cocaine were compared. We have evaluated in these models tropane derivatives synthesized with original synthons which coupled properties of both fluorine and iodine atoms. One compound showed a high in vitro affinity and selectivity for the DAT (K(i)=0.87±0.04 nM). This compound should be radiolabeled with radioiodine for further investigations by SPECT.

Analytical Methodology for a Metabolome Atlas of Goat's Plasma, Milk and Feces Using 1H-NMR and UHPLC-HRMS.

Metabolomics has been increasingly used in animal and food sciences. Animal health is one of the most important factor that can also alter animal integrity and welfare. Some studies have already investigated the link between health and metabolic profile of dairy animals. These studies in metabolomics often consider a single type of sample using a single analytical platform (nuclear magnetic resonance or mass spectrometry). Only few studies with multi-platform approaches are also used with a single or a multi type of sample, but they mainly consider dairy cows' metabolome although dairy goats present similar diseases, that it could be interesting to detect early to preserve animal health and milk production. This study aims to create a metabolic atlas of goat plasma, milk and feces, based on healthy animals. Our study describes a standard operating procedure for three goat matrices: blood plasma, milk, and feces using multiple platforms (NMR (1H), UHPLC (RP)-MS and UHPLC (HILIC)-MS) that follows a unique sample preparation procedure for each sample type to be analyzed on multi-platforms basis. Our method was evaluated for its robustness and allowed a better characterization of goat metabolic profile in healthy conditions.

The contributions of metabolomics in the discovery of new therapeutic targets in Alzheimer's disease.

Alzheimer's disease (AD) leads to the progressive loss of memory and other cognitive functions. It is the most common form of dementia in the elderly and has become a major public health problem due to the increase in life expectancy. Although the detection of AD is based on several neuropsychological tests, imaging, and biological analyses, none of these biomarkers allows a clear understanding of the pathophysiological mechanisms involved in the disease, and no efficient treatment is currently available. Metabolomics, which allows the study of biochemical alterations underlying pathological processes, could help to identify these mechanisms, to discover new therapeutic targets, and to monitor the therapeutic response and disease progression. In this review, we have summarized and analyzed the results from a number of studies on metabolomics analyses performed in biological samples originated from the central nervous system, in AD subjects, and in animal models of this disease. This synthesis revealed modified expression of specific metabolites in pathological conditions which allowed the identification of significantly impacted metabolic pathways both in animals and humans, such as the arginine biosynthesis and the alanine, aspartate, and glutamate metabolism. We discuss the potential biochemical mechanisms involved, the extent to which they could impact the specific hallmarks of AD, and the therapeutic approaches which could be proposed as a result.

SHR/NCrl rats as a model of ADHD can be discriminated from controls based on their brain, blood, or urine metabolomes.

Attention-Deficit Hyperactivity Disorder (ADHD) is one of the most common neurodevelopmental disorder characterized by inattention, impulsivity, and hyperactivity. The neurobiological mechanisms underlying ADHD are still poorly understood, and its diagnosis remains difficult due to its heterogeneity. Metabolomics is a recent strategy for the holistic exploration of metabolism and is well suited for investigating the pathophysiology of diseases and finding molecular biomarkers. A few clinical metabolomic studies have been performed on peripheral samples from ADHD patients but are limited by their access to the brain. Here, we investigated the brain, blood, and urine metabolomes of SHR/NCrl vs WKY/NHsd rats to better understand the neurobiology and to find potential peripheral biomarkers underlying the ADHD-like phenotype of this animal model. We showed that SHR/NCrl rats can be differentiated from controls based on their brain, blood, and urine metabolomes. In the brain, SHR/NCrl rats displayed modifications in metabolic pathways related to energy metabolism and oxidative stress further supporting their importance in the pathophysiology of ADHD bringing news arguments in favor of the Neuroenergetic theory of ADHD. Besides, the peripheral metabolome of SHR/NCrl rats also shared more than half of these differences further supporting the importance of looking at multiple matrices to characterize a pathophysiological condition of an individual. This also stresses out the importance of investigating the peripheral energy and oxidative stress metabolic pathways in the search of biomarkers of ADHD.

Deletion of Mocos Induces Xanthinuria with Obstructive Nephropathy and Major Metabolic Disorders in Mice.

Background: Xanthinuria type II is a rare autosomal purine disorder. This recessive defect of purine metabolism remains an under-recognized disorder. Methods: Mice with targeted disruption of the molybdenum cofactor sulfurase (Mocos) gene were generated to enable an integrated understanding of purine disorders and evaluate pathophysiologic functions of this gene which is found in a large number of pathways and is known to be associated with autism. Results: Mocos-deficient mice die with 4 weeks of age due to renal failure of distinct obstructive nephropathy with xanthinuria, xanthine deposits, cystic tubular dilation, Tamm-Horsfall (uromodulin) protein (THP) deposits, tubular cell necrosis with neutrophils, and occasionally hydronephrosis with urolithiasis. Obstructive nephropathy is associated with moderate interstitial inflammatory and fibrotic responses, anemia, reduced detoxification systems, and important alterations of the metabolism of purines, amino acids, and phospholipids. Conversely, heterozygous mice expressing reduced MOCOS protein are healthy with no apparent pathology. Conclusions: Mocos-deficient mice develop a lethal obstructive nephropathy associated with profound metabolic changes. Studying MOCOS functions may provide important clues about the underlying pathogenesis of xanthinuria and other diseases requiring early diagnosis.

Synthesis and in vitro evaluation of fluorinated diphenyloxide derivatives and sulfur analogs as serotonin transporter ligands.

As the serotonin transporter (SERT) is involved in several neurodegenerative and psychiatric disorders; radiopharmaceuticals to image the SERT by PET would be valuable in studying these diseases. To this end we synthesized diphenyloxide derivatives and sulfide analogs, as new tracers, incorporating a fluorine or oxyalkyl fluorinated group on 4' or 5'-position on phenyl ring B. Three of these exhibited good to high in vitro affinity (7

3D QSAR study, synthesis, and in vitro evaluation of (+)-5-FBVM as potential PET radioligand for the vesicular acetylcholine transporter (VAChT).

Located in presynaptic cholinergic nerve terminals, the vesicular acetylcholine transporter (VAChT) represents a potential target for quantitative visualization of early degeneration of cholinergic neurons in Alzheimer's disease using PET. Benzovesamicol derivatives are proposed as radioligands for this purpose. We report QSAR studies of vesamicol and benzovesamicol derivatives taking into account the stereoselectivity of the VAChT binding site. Use of different data sets and different models in this study revealed that both enantiomers of 5-fluoro-3-(4-phenyl-piperidin-1-yl)-1,2,3,4-tetrahydro-naphthalen-2-ol (5-FBVM) are promising candidates, with predicted VAChT affinities between 6.1 and 0.05 nM. The synthesis of enantiopure (R,R)- and (S,S)-5-FBVM and their corresponding triazene precursors for future radiofluorination is reported. Both enantiomers exhibited high in vitro affinity for VAChT [(+)-5-FBVM: K(i)=6.95 nM and (-)-5-FBVM: K(i)=3.68 nM] and were selective for σ(2) receptors (∼70-fold), only (+)-5-FBVM is selective for σ(1) receptors (∼fivefold). These initial results suggest that (+)-(S,S)-5-FBVM warrants further investigation as a potential radioligand for in vivo PET imaging of cholinergic nerve terminals.

Validation of a global quantitative analysis methodology of tryptophan metabolites in mice using LC-MS.

In this study, we validated a method for quantifying 20 tryptophan (Trp) catabolites by liquid chromatography coupled with high resolution mass spectrometry (LC-HRMS) in 4 different matrices (urine, serum, intestinal contents and liver). The detection limit for all metabolites ranged between 0.015 and 11.25 nmol/L and the dynamic range of the calibration curves were adjusted to allow quantification of metabolites at endogenous levels. Matrix effects were evaluated using isotope labeled internal standards. Reproducibility in the 4 matrices was characterized by CV = 6.2% with an accuracy of 6.6%. Our method has been applied to the determination and quantification of 20 metabolites concentrations in 5 different mouse compartments (plus cecal contents). Our results show that our approach allows for a global exploration of the Trp metabolism by quantifying a large number of Trp metabolites, at the individual level by multi-matrix approach.

Docking study, synthesis, and in vitro evaluation of fluoro-MADAM derivatives as SERT ligands for PET imaging.

In order to predict affinity of new diphenylsulfides for the serotonin transporter (SERT), a molecular modeling model was used to compare potential binding affinity of new compounds with known potent ligands. The aim of this study is to identify a suitable PET radioligand for imaging the SERT, new derivatives, and their precursors for a C-11 or F-18 radiolabeling, were synthesized. Two fluorinated derivatives displayed good in vitro affinity for the SERT (K(i)=14.3+/-1 and 10.1+/-2.7 nM) and good selectivity toward the other monoamine transporters as predicted by the docking study.

Validation of metabolomics analysis of human perilymph fluid using liquid chromatography-mass spectroscopy.

Although there is some data from animal studies, the metabolome of inner ear fluid in humans remains unknown. Characterization of the metabolome of the perilymph would allow for better understanding of its role in auditory function and for identification of biomarkers that might allow prediction of response to therapeutics. There is a major technical challenge due to the small sample of perilymph fluid available for analysis (sub-microliter). The objectives of this study were to develop and validate a methodology for analysis of perilymph metabolome using liquid chromatography-high resolution mass spectrometry (LC-HRMS). Due to the low availability of perilymph fluid; a methodological study was first performed using low volumes (0.8 µL) of cerebrospinal fluid (CSF) and optimized the LC-HRMS parameters using targeted and non-targeted metabolomics approaches. We obtained excellent parameters of reproducibility for about 100 metabolites. This methodology was then used to analyze perilymph fluid using two complementary chromatographic supports: reverse phase (RP-C18) and hydrophilic interaction liquid chromatography (HILIC). Both methods were highly robust and showed their complementarity, thus reinforcing the interest to combine these chromatographic supports. A fingerprinting was obtained from 98 robust metabolites (analytical variability <30%), where amino acids (e.g., asparagine, valine, glutamine, alanine, etc.), carboxylic acids and derivatives (e.g., lactate, carnitine, trigonelline, creatinine, etc.) were observed as first-order signals. This work lays the foundations of a robust analytical workflow for the exploration of the perilymph metabolome dedicated to the research of biomarkers for the diagnosis/prognosis of auditory pathologies.